Local Path Planning for Unmanned Ground Vehicles Based on Improved Artificial Potential Field Method in Frenet Coordinate System

The artificial potential field method is widely used in the local path planning for unmanned ground vehicle (UGV) due to its small amount of computation and high accuracy. For the problems of target unreachability, local minimum and falling into U鄄shaped obstacles existing in the conventional artificial potential field method, a local path planning algorithm based on the improved artificial potential field method in Frenet coordinate system is proposed. In this paper, the Frenet coordinate system is used to describe the UGV蒺s obstacle avoidance movement, which simplifies the planning model and addresses the difficulty in expressing the relative position of UGV and the road during path planning. A safety ellipse model and the concept of prediction distance are proposed to adjust the influence area of the potential field. Additionally, the repulsive field function is improved by adding the reference line potential field and the dynamic velocity potential field based on the Frenet coordinate system. These modifications enable the UGVs to avoid obstacles under both static and dynamic conditions. The path planning methods are proposed to launch the static and dynamic obstacle avoidance simulation experiments with different vehicle speeds in straight and curved road scenarios using mathematical simulation software. The results demonstrate that the front wheel turning angle and traverse angular velocity at different vehicle speeds are controlled within a small range, and the improved algorithm can effectively solve the defects of the conventional artificial potential field method. Besides, compared with the rapidly鄄exploring random tree(RRT) algorithm, the computational efficiency of path planning of the improved algorithm in the obstacle avoidance process is improved by 42郾 8%, and achieves better computational performance. © 2024 China Ordnance Industry Corporation. All rights reserved.